A Wentzell-Freidlin type large deviation principle is established for the two-dimensional Navier-Stokes equations perturbed by a multiplicative noise in both bounded and unbounded domains. The large deviation principle is equivalent to the Laplace principle in our function space setting. Hence, the weak convergence approach is employed to obtain the Laplace principle for solutions of stochastic Navier-Stokes equations. The existence and uniqueness of a strong solution to (a) stochastic Navier-Stokes equations with a small multiplicative noise, and (b) Navier-Stokes equations with an additional Lipschitz continuous drift term are proved for unbounded domains which may be of independent interest. © 2006 Elsevier Ltd. All rights reserved
International audienceWe deal with a class of abstract nonlinear stochastic models, which covers man...
International audienceWe deal with a class of abstract nonlinear stochastic models, which covers man...
International audienceWe deal with a class of abstract nonlinear stochastic models, which covers man...
AbstractA Wentzell–Freidlin type large deviation principle is established for the two-dimensional Na...
AbstractA Wentzell–Freidlin type large deviation principle is established for the two-dimensional Na...
AbstractIn this paper, we establish a large deviation principle for the two-dimensional stochastic N...
Röckner M, Zhang T, Zhang X. Large Deviations for Stochastic Tamed 3D Navier-Stokes Equations. Appli...
Abstract. In this paper, using weak convergence method, we prove a large deviation principle of Frei...
The aim of this paper is threefold. Firstly, we prove the existence and the uniqueness of a global s...
International audienceUsing a weak convergence approach, we prove a LPD for the solution of 2D stoch...
International audienceUsing a weak convergence approach, we prove a LPD for the solution of 2D stoch...
International audienceUsing a weak convergence approach, we prove a LPD for the solution of 2D stoch...
International audienceWe deal with a class of abstract nonlinear stochastic models, which covers man...
International audienceWe deal with a class of abstract nonlinear stochastic models, which covers man...
International audienceWe deal with a class of abstract nonlinear stochastic models, which covers man...
International audienceWe deal with a class of abstract nonlinear stochastic models, which covers man...
International audienceWe deal with a class of abstract nonlinear stochastic models, which covers man...
International audienceWe deal with a class of abstract nonlinear stochastic models, which covers man...
AbstractA Wentzell–Freidlin type large deviation principle is established for the two-dimensional Na...
AbstractA Wentzell–Freidlin type large deviation principle is established for the two-dimensional Na...
AbstractIn this paper, we establish a large deviation principle for the two-dimensional stochastic N...
Röckner M, Zhang T, Zhang X. Large Deviations for Stochastic Tamed 3D Navier-Stokes Equations. Appli...
Abstract. In this paper, using weak convergence method, we prove a large deviation principle of Frei...
The aim of this paper is threefold. Firstly, we prove the existence and the uniqueness of a global s...
International audienceUsing a weak convergence approach, we prove a LPD for the solution of 2D stoch...
International audienceUsing a weak convergence approach, we prove a LPD for the solution of 2D stoch...
International audienceUsing a weak convergence approach, we prove a LPD for the solution of 2D stoch...
International audienceWe deal with a class of abstract nonlinear stochastic models, which covers man...
International audienceWe deal with a class of abstract nonlinear stochastic models, which covers man...
International audienceWe deal with a class of abstract nonlinear stochastic models, which covers man...
International audienceWe deal with a class of abstract nonlinear stochastic models, which covers man...
International audienceWe deal with a class of abstract nonlinear stochastic models, which covers man...
International audienceWe deal with a class of abstract nonlinear stochastic models, which covers man...